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Robust analysis of MRS brain tumour data using t-GTM

Autor
Vellido, A.; Lisboa, P.; Vicente, D.
Tipus d'activitat
Article en revista
Revista
Neurocomputing
Data de publicació
2006-03
Volum
69
Número
7-9
Pàgina inicial
754
Pàgina final
768
DOI
https://doi.org/10.1016/j.neucom.2005.12.005 Obrir en finestra nova
URL
http://www.sciencedirect.com/science/article/pii/S0925231205003103 Obrir en finestra nova
Resum
This paper proposes a principled, self-organized, framework to manage two sources of uncertainty that are inherent in intelligent systems for medical decision support, namely outliers and missing data. The framework is applied to magnetic resonance spectra (MRS), which are indicators of the grade of malignancy in brain tumours. A model for multivariate data clustering and visualization, the generative topographic mapping (GTM), is re-formulated as a mixture of Student's t-distributions making it...
Paraules clau
Generative Topographic Mapping, Magnetic Resonance Spectroscopy, Outliers, Missing Data, Feature Relevance Determination
Grup de recerca
IDEAI-UPC Intelligent Data Science and Artificial Intelligence
SOCO - Soft Computing

Participants